ABSTRACT
The term artificial intelligence (AI) often emphasizes the software aspects, while the term robot includes a physical body as an important part. The notions of AI and robotics come from a long way back. In the first wave of AI, domain-experts devised algorithms and software according to available knowledge. This approach led to the creation of chessplaying computers, and of delivery optimization software. In summary, first-wave AI systems are capable of implementing logical rules for well-defined problems but are incapable of learning, and not able to deal with problems with a large underlying uncertainty. A typical example of unsupervised learning is a self-organizing map in data visualization. Reinforcement learning is an active area in artificial intelligence study or machine learning that concerns how a learner should take actions in an environment so as to maximize some notion of long-term reward. Swarm intelligence is not an “accident” but rather a property of complex systems.
